diff --git a/R/rmtd.R b/R/rmtd.R
index 3b8c7d631ef9f14d2faa90a8cb1dbd62fceff6eb..437d0482071bae61b53058523bf95c8c336f7c68 100644
--- a/R/rmtd.R
+++ b/R/rmtd.R
@@ -19,7 +19,7 @@ rmtd <- function(n, nu, mu, Sigma, tol = 1e-6) {
   #' can be generated using:
   #' \deqn{\displaystyle{X = \mu + \frac{Y}{\sqrt{\frac{u}{\nu}}}}}
   #' where \eqn{Y} is a random vector distributed among a centered Gaussian density
-  #' with covariance matrix \eqn{\Sigma} (generated using \code{\link{mvrnorm}})
+  #' with covariance matrix \eqn{\Sigma} (generated using \code{\link[MASS]{mvrnorm}})
   #' and \eqn{u} is distributed among a Chi-squared distribution with \eqn{\nu} degrees of freedom.
   #'
   #' @author Pierre Santagostini, Nizar Bouhlel
diff --git a/man/rmtd.Rd b/man/rmtd.Rd
index fb5a080b8c4b3b177bf43ed0c8759134757a3061..e1155e8e828f38851a80cb56b7b4151e200fe5c8 100644
--- a/man/rmtd.Rd
+++ b/man/rmtd.Rd
@@ -30,7 +30,7 @@ A sample from a MTD with parameters \eqn{\nu}, \eqn{\boldsymbol{\mu}} and \eqn{\
 can be generated using:
 \deqn{\displaystyle{X = \mu + \frac{Y}{\sqrt{\frac{u}{\nu}}}}}
 where \eqn{Y} is a random vector distributed among a centered Gaussian density
-with covariance matrix \eqn{\Sigma} (generated using \code{\link{mvrnorm}})
+with covariance matrix \eqn{\Sigma} (generated using \code{\link[MASS]{mvrnorm}})
 and \eqn{u} is distributed among a Chi-squared distribution with \eqn{\nu} degrees of freedom.
 }
 \examples{